Worldwide, millions of people are locked in or in a wheelchair, due to several neuromuscular disorders or spinal cord injuries. These individuals are deprived of trivial social activities, like interacting or playing games with other people. Such activities are crucial for personal development, and can have a great impact on the quality of their lives. This work aims at the design and implementation of an electroencephalography (EEG) based motor imagery (MI) brain computer interface (BCI) system that would allow disabled, and able-bodied, individuals alike to control a drone in a 3D physical environment by only using their thoughts. An improved version of the filter bank common spatial pattern (FBCSP) algorithm was developed, and it has shown to perform superior (68.5% accuracy) to the winning FBCSP algorithm (67.8% accuracy), when tested on dataset 2a (4 class MI) of the BCI competition IV. A deep convolutional neural network (CNN) based algorithm was also implemented and tested on the same dataset, which however performed inferior (62.9% accuracy) to the winner, as well as our proposed FBCSP algorithms. The improved FBCSP was then tested on our inhouse 5-class (left hand, right hand, tongue, both feet and rest) MI dataset (collected from 10 able-bodied subjects) and obtained a mean accuracy of 41.8±11.74%. This is considered a significant result though it is not good enough to attempt the control of a real drone.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    An Improved Five Class MI Based BCI Scheme for Drone Control Using Filter Bank CSP



    Erscheinungsdatum :

    2019-01-01


    Anmerkungen:

    Christensen , S M , Holm , N S & Puthusserypady , S 2019 , An Improved Five Class MI Based BCI Scheme for Drone Control Using Filter Bank CSP . in Proceedings of 2019 7th International Winter Conference on Brain-Computer Interface . IEEE , 7th International Winter Conference on Brain-Computer Interface , Jeongseon , Korea, Republic of , 18/02/2019 . https://doi.org/10.1109/IWW-BCI.2019.8737263



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    006 / 629



    IMPROVED DRONE

    Europäisches Patentamt | 2021

    Freier Zugriff

    IMPROVED DRONE

    KIM HAK MIN / HONG JIN WOO / LEE HAN SUNG et al. | Europäisches Patentamt | 2016

    Freier Zugriff

    DRONE, DRONE STATION, AND DRONE TAKE-OFF CONTROL METHOD USING DRONE STATION

    YI SEOKHEE / SEO JEONGKYO / KIM NAKYEONG | Europäisches Patentamt | 2021

    Freier Zugriff

    IMPROVED HYBRID DRONE

    LEE HO HYEONG / LEE WAN HYEONG | Europäisches Patentamt | 2019

    Freier Zugriff

    DRONE, DRONE CONTROL METHOD, AND DRONE CONTROL PROGRAM

    WAKE CHIHIRO / YANAGISHITA HIROSHI | Europäisches Patentamt | 2019

    Freier Zugriff